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Low-cohesion differential privacy protection for industrial Internet

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Abstract

Due to the increasing intelligence of data acquisition and analysis in cyber physical systems (CPSs) and the emergence of various transmission vulnerabilities, this paper proposes a differential privacy protection method for frequent pattern mining in view of the application-level privacy protection requirements of industrial interconnected systems. This method designs a low-cohesion algorithm to realize differential privacy protection. In the implementation of differential privacy protection, Top-k frequent mode method is introduced, which combines the factors of index mechanism and low cohesive weight of each mode, and the original support of each selected mode is disturbed by Laplacian noise. It achieves a balance between privacy protection and utility, guarantees the trust of all parties in CPS and provides an effective solution to the problem of privacy protection in industrial Internet systems.

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    http://fimi.ua.ac.be/data/.

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Acknowledgements

This paper supported by The Fundamental Research Funds for the Central Universities (No. 30918012204, Military Common Information System Equipment Pre-research Special Technology Project (315075701), 2019 Industrial Internet Innovation and Development Project from Ministry of Industry and Information Technology of China, 2018 Jiangsu Province Major Technical Research Project “Information Security Simulation System”, and Shanghai Aerospace Science and Technology Innovation Fund (SAST2018-103).

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Correspondence to Qianmu Li.

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Hou, J., Li, Q., Cui, S. et al. Low-cohesion differential privacy protection for industrial Internet. J Supercomput (2020). https://doi.org/10.1007/s11227-019-03122-y

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Keywords

  • Differential privacy protection
  • Industrial Internet
  • CPS